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The goal of this thesis is to identify measurement, modeling, and optimization opportunities for large scale networks -- with specific focus on cellular networks and online social networks. These networks are facing unprecedented operational challenges due to their very large scale.Cellular networks are experiencing an explosive increase in the volume of traffic for the last few years. This unprecedented increase in the volume of mobile traffic is attributed to the increase in the subscriber... Show moreThe goal of this thesis is to identify measurement, modeling, and optimization opportunities for large scale networks -- with specific focus on cellular networks and online social networks. These networks are facing unprecedented operational challenges due to their very large scale.Cellular networks are experiencing an explosive increase in the volume of traffic for the last few years. This unprecedented increase in the volume of mobile traffic is attributed to the increase in the subscriber base, improving network connection speeds, and improving hardware and software capabilities of modern smartphones. In contrast to the traditional fixed IP networks, mobile network operators are faced with the constraint of limited radio frequency spectrum at their disposal. As the communication technologies evolve beyond 3G to Long Term Evolution (LTE), the competition for the limited radio frequency spectrum is becoming even more intense. Therefore, mobile network operators increasingly focus on optimizing different aspects of the network by customized design and management to improve key performance indicators (KPIs).Online social networks are increasing at a very rapid pace, while trying to provide more content-rich and interactive services to their users. For instance, Facebook currently has more than 1.2 billion monthly active users and offers news feed, graph search, groups, photo sharing, and messaging services. The information for such a large user base cannot be efficiently and securely managed by traditional database systems. Social network service providers are deploying novel large scale infrastructure to cope with these scaling challenges.In this thesis, I present novel approaches to tackle these challenges by revisiting the current practices for the design, deployment, and management of large scale network systems using a combination of theoretical and empirical methods. I take a data-driven approach in which the theoretical and empirical analyses are intertwined. First, I measure and analyze the trends in data and then model the identified trends using suitable parametric models. Finally, I rigorously evaluate the developed models and the resulting system design prototypes using extensive simulations, realistic testbed environments, or real-world deployment. This methodology is to used to address several problems related to cellular networks and online social networks. Show less